ML Fundamentals

DeepMind x UCL | Deep Learning Lectures | 6/12 | Sequences and Recurrent Networks

DeepMind x UCL | Deep Learning Lectures | 3/12 | Convolutional Neural Networks for Image Recognition

Engineering a Less Artificial Intelligence with Andreas Tolias - #379

Benchmarks for collaborative Machine Learning with Stacey Svetlichnaya

Linear Algebra Ep 2 | Dot Product in Linear Algebra for Data Science

Model monitoring with Fury Data Apps at Mercado Libre

ML platform Fury Data Apps at Mecado Libre

25. Structure of set addition V: additive energy and Balog-Szemerédi-Gowers theorem

4. Forbidding a subgraph III: algebraic constructions

My Laptop Lenovo Legion Y 540 Performance After Using 1 Month

BERT Neural Network - EXPLAINED!

Surprising Utility of Surprise: Why ML Uses Negative Log Probabilities - Charles Frye

Neural Network from Scratch - Machine Learning Python

AI Weekly Update - April 27th, 2020 (#19)

SVM from Scratch - Machine Learning Python (Support Vector Machine)

Supervised Contrastive Learning

Lessons from Crisis Management: Rapid Innovation

How do GPUs speed up Neural Network training?

Advanced Theory | Neural Style Transfer #4

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

AR Model Code Example : Time Series Talk

Inside TensorFlow: tf.data + tf.distribute

Distributed TensorFlow model training on Cloud AI Platform (TF Dev Summit '20)

DeepMind x UCL | Deep Learning Lectures | 1/12 | Intro to Machine Learning & AI

DeepMind x UCL | Deep Learning Lectures | 5/12 | Optimization for Machine Learning

DeepMind x UCL | Deep Learning Lectures | 2/12 | Neural Networks Foundations

What parts of the mercado libre ML platforms are automatted

Litox View of the state of ML today

Fury Platform and Fury Data Apps at Mercado Libre

MLOps community meetup #11 // Machine Learning at Scale in Mercado Libre with Carlos de la Torre

22. Structure of set addition II: groups of bounded exponent and modeling lemma

6. Szemerédi's graph regularity lemma I: statement and proof

11. Pseudorandom graphs I: quasirandomness

2. Forbidding a subgraph I: Mantel's theorem and Turán's theorem

15. Graph limits II: regularity and counting

24. Structure of set addition IV: proof of Freiman's theorem

5. Forbidding a subgraph IV: dependent random choice

7. Szemerédi's graph regularity lemma II: triangle removal lemma

18. Roth's theorem I: Fourier analytic proof over finite field

17. Graph limits IV: inequalities between subgraph densities

26. Sum-product problem and incidence geometry

Training ML models on live datasets in a GDPR world

Naive Bayes from Scratch - Machine Learning Python

Pytorch LeNet implementation from scratch

How Linear Algebra is not like Algebra with Charles Frye

Testing Machine Learning Models with Eric Schles

Optimize your models with TF Model Optimization Toolkit (TF Dev Summit '20)

TensorFlow Extended (TF Dev Summit '20)